Abstract 541: PARP and autophagy inhibition synergy in small cell lung cancer
Notice bibliographique
Résumé
Abstract Purpose: Small cell lung cancer (SCLC) is a high-grade neuroendocrine carcinoma comprising 15% of lung cancers. First-line treatment with platinum and etoposide chemotherapy—and radiotherapy for limited stage disease—produces good initial response, but most patients suffer treatment-resistant relapse within 2 years. The median survival is under 10 months, with immunotherapy increasing this by about 2 months. This regimen has changed minimally in 3 decades, fueling a need for more effective therapies. Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) effectively induce DNA damage in SCLC and have shown potential in this setting, but response is variable, so we aimed to identify mechanisms through which SCLC may be sensitized to PARPi therapy. Methods: CRISPR dropout screens were conducted using the Toronto KnockOut v1 (TKOv1) CRISPR library in the SBC5 and H82 SCLC cell lines, with the PARPi, olaparib, as the selection pressure. DNA sequencing was performed at days 25 and 35 for SBC5 and days 28 and 39 for H82. Top hits were identified by gene dropout in the olaparib condition versus the control, with a false discovery rate (FDR) cutoff of 0.05. Gene ontology analysis was used to identify critical pathways. Stable shRNA knockdown cell lines were generated using lentiviral transduction and validated by Western blot. Cells were treated with olaparib and assayed for viability with CellTiter-Glo 2.0. In wild-type cell lines, therapeutic mTOR activation with MHY1485 was validated by Western blot and therapeutic autophagy inhibition with chloroquine (CQ) or GNS561 was validated by Western blot after 3 hours starvation in EBSS medium. Efficacy of autophagy inhibitors alone and in combination with PARPi was assayed by cell viability, and SynergyFinder+ was used to quantify synergism of the combination. Results: CRISPR screening identified mTOR pathway regulators, including components of the TSC and GATOR1 complexes, and gene ontology analysis indicated downregulation of TOR signaling and upregulation of autophagy as key pathways which confer PARPi sensitivity when lost. TSC1/2 knockdown cell lines exhibit reduced viability after PARPi treatment. MHY1485 treatment blocked autophagy as indicated by LC3B-II accumulation, but combination therapy with MHY1485 and olaparib was antagonistic due to proliferative effects of MHY1485. CQ or GNS561 treatment also blocked autophagy, and SCLC cell lines had varying sensitivity to these agents as monotherapies. Autophagy inhibition synergized with PARPi, sensitizing SCLC cell lines to PARPi therapy. Conclusions: TSC1/2 knockdown sensitizes SCLC cell lines to PARPi in concordance with our model that mTOR downregulation promotes autophagy and cell survival after PARPi therapy. While mTOR upregulation was antagonistic with PARPi and promoted cell growth, autophagy inhibitors were a superior therapeutic approach, synergizing with PARPi in vitro. Citation Format: Tony Yu, Ranya Barayan, Lifang Song, Vidhyasagar Venkatasubramanian, Sree N. Nair, Vivek Philip, Benjamin H. Lok. PARP and autophagy inhibition synergy in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 541.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».